| dc.contributor.author | Johnson, Eric | |
| dc.contributor.author | Abushagur, Mustafa | |
| dc.date.accessioned | 2009-02-24T21:12:34Z | |
| dc.date.available | 2009-02-24T21:12:34Z | |
| dc.date.issued | 1997-07-15 | |
| dc.identifier.uri | http://hdl.handle.net/1850/8494 | |
| dc.description | RIT community members may access full-text via RIT Libraries licensed databases: http://library.rit.edu/databases/ | |
| dc.description.abstract | Image deconvolution is addressed using a modified Genetic Algorithm for the error minimization. Numerical examples
are presented to demonstrate the algorithm’s robustness. Specifically, noise levels and various regions of support are
investigated to verify the approach to the blind deconvolution problem of two positively constrained images. Good results
were obtained using the algorithm in recovering images from their convolutions without any a priori information, other than
the maximum bounds on their regions of support. | en_US |
| dc.language.iso | en_US | en_US |
| dc.publisher | Elsevier - Optics Communications | en_US |
| dc.relation.ispartofseries | Vol. 130 | en_US |
| dc.relation.ispartofseries | No. 1-3 | en_US |
| dc.subject | Design optimization | en_US |
| dc.subject | Image deconvolution | en_US |
| dc.subject | Image filtering | en_US |
| dc.subject | Image processing | en_US |
| dc.title | Image deconvolution using a micro genetic algorithm | en_US |
| dc.type | Article | en_US |
| dc.identifier.url | http://dx.doi.org/10.1016/S0030-4018(97)00164-8 | |
